code: def set_cudnn_batchnorm_mode():
      """Set CuDNN batchnorm mode for better performance.
  
      Note: Spatial Persistent mode may lead to accuracy losses for certain
      models.
      """
      if FLAGS.batchnorm_spatial_persistent:
          os.environ["TF_USE_CUDNN_BATCHNORM_SPATIAL_PERSISTENT"] = "1"
      else:
          os.environ.pop(
              "TF_USE_CUDNN_BATCHNORM_SPATIAL_PERSISTENT", None
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  import tensorflow
  from tensorflow.python.keras.optimizer_v2 import gradient_descent
  from utils.flags import core
  from utils.misc import keras_utils
label_desc: Use image node_id 8 for calling a global function with example usage: set_cudnn_batchnorm_mode() without return types